| Brain tumor segmentation with deep neural networks M Havaei, A Davy, D Warde-Farley, A Biard, A Courville, Y Bengio, C Pal, ... Medical image analysis 35, 18-31, 2017 | 2604 | 2017 |
| ISLES 2015-A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI O Maier, BH Menze, J von der Gablentz, L Häni, MP Heinrich, M Liebrand, ... Medical image analysis 35, 250-269, 2017 | 379 | 2017 |
| Hemis: Hetero-modal image segmentation M Havaei, N Guizard, N Chapados, Y Bengio International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 179 | 2016 |
| A convolutional neural network approach to brain tumor segmentation M Havaei, F Dutil, C Pal, H Larochelle, PM Jodoin BrainLes 2015, 195-208, 2015 | 101 | 2015 |
| Deep learning trends for focal brain pathology segmentation in MRI M Havaei, N Guizard, H Larochelle, PM Jodoin Machine learning for health informatics, 125-148, 2016 | 92 | 2016 |
| Efficient interactive brain tumor segmentation as within-brain kNN classification M Havaei, PM Jodoin, H Larochelle 2014 22nd international conference on pattern recognition, 556-561, 2014 | 77 | 2014 |
| Implicit class-conditioned domain alignment for unsupervised domain adaptation X Jiang, Q Lao, S Matwin, M Havaei International Conference on Machine Learning, 4816-4827, 2020 | 63 | 2020 |
| CAGNet: Content-aware guidance for salient object detection S Mohammadi, M Noori, A Bahri, SG Majelan, M Havaei Pattern Recognition 103, 107303, 2020 | 52 | 2020 |
| Learning to learn with conditional class dependencies X Jiang, M Havaei, F Varno, G Chartrand, N Chapados, S Matwin international conference on learning representations, 2018 | 48 | 2018 |
| Within-brain classification for brain tumor segmentation M Havaei, H Larochelle, P Poulin, PM Jodoin International journal of computer assisted radiology and surgery 11 (5), 777-788, 2016 | 48 | 2016 |
| Infomask: Masked variational latent representation to localize chest disease SA Taghanaki, M Havaei, T Berthier, F Dutil, LD Jorio, G Hamarneh, ... International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 31 | 2019 |
| Dual adversarial inference for text-to-image synthesis Q Lao, M Havaei, A Pesaranghader, F Dutil, LD Jorio, T Fevens Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 28 | 2019 |
| Learnable explicit density for continuous latent space and variational inference CW Huang, A Touati, L Dinh, M Drozdzal, M Havaei, L Charlin, ... arXiv preprint arXiv:1710.02248, 2017 | 28 | 2017 |
| Continuous domain adaptation with variational domain-agnostic feature replay Q Lao, X Jiang, M Havaei, Y Bengio arXiv preprint arXiv:2003.04382, 2020 | 20 | 2020 |
| DFNet: Discriminative feature extraction and integration network for salient object detection M Noori, S Mohammadi, SG Majelan, A Bahri, M Havaei Engineering Applications of Artificial Intelligence 89, 103419, 2020 | 18 | 2020 |
| Attentive task-agnostic meta-learning for few-shot text classification X Jiang, M Havaei, G Chartrand, H Chouaib, T Vincent, A Jesson, ... | 14 | 2018 |
| A convolutional neural network approach to brain lesion segmentation F Dutil, M Havaei, C Pal, H Larochelle, P Jodoin Ischemic Stroke Lesion Segment 9556, 51-6, 2015 | 13 | 2015 |
| On the importance of attention in meta-learning for few-shot text classification X Jiang, M Havaei, G Chartrand, H Chouaib, T Vincent, A Jesson, ... arXiv preprint arXiv:1806.00852, 2018 | 11 | 2018 |
| Conditional generation of medical images via disentangled adversarial inference M Havaei, X Mao, Y Wang, Q Lao Medical Image Analysis 72, 102106, 2021 | 9 | 2021 |
| Task adaptive metric space for medium-shot medical image classification X Jiang, L Ding, M Havaei, A Jesson, S Matwin International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 9 | 2019 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARDirección de correo verificada de umontreal.ca
